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How can I interpret the evaluation results for my regression model?

For regression models, the evaluation results are based on the following metrics or measures:

  • Mean Absolute Error: it tells you how close the predictions are to the actual outcomes.
  • Mean Squared Error: it is like absolute error, but it will give a little more weight to the large errors.
  • R Squared: it tells you how much better the model’s prediction is than just predicting the mean target value all the time.


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